JobScout

I built a private job-intelligence platform with normalized data paths and workflow support for engineering recruiting.

01 Overview

What I’m building

I’m building JobScout as a private full-stack platform for job data normalization and recruiting workflows.

I use JobScout as a private recruiting operations tool for engineering opportunities.

I use it to normalize and deduplicate incoming jobs, then support controlled review and candidate-facing planning.

I’m keeping the product private while I plan its standalone separation.

02 Challenge

I need reliable job records across collection, deduplication, and workflow use.

I needed consistent ingestion despite varied source structures.

I normalized jobs to improve review quality and reduce duplicate tracking noise.

I also needed backups, exports, and controlled environment handling in the architecture.

03 Process

I’m combining backend pipelines, a typed frontend, and deployment automation.

I’m using FastAPI services, SQLAlchemy models, deduplication logic, scheduled processing, and reliable import and export paths on the backend.

On the frontend, I’m using Next.js and React with typed interfaces and workflow views to review job records.

I’m handling containerized deployment patterns, migration handling, and security hardening for production settings.

04 Outcome

I’m keeping JobScout in active development with a stable private deployment while I refine its architecture.

I’m actively improving the private product before I finalize a standalone domain.

I’m organizing it around workflow efficiency and candidate and job operations rather than a static catalog.